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The potential of a small model

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  • Adam Elbourne

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  • Coen Teulings

Abstract

This CPB Discussion Paper highlights potential uses of simple, small models where large traditional models are less flexible. (updated 22/12/2011). We run a number of experiments with a small two variable VAR model of GDP growth and unemployment with both quarterly and yearly data. We compare the forecasts of these simple models with the published forecasts of the CPB and we conclude that there is not much di erence. We then show how easy it is to evaluate the usefulness of a given variable for forecasting by extending the model to include world trade. Perfect knowledge of future world trade growth would help considerably but is obviously not available at the time the forecasts were made. The available world trade data doesn't improve the forecasts. Finally we also show how quick and exible measures of the output gap can be constructed.

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Bibliographic Info

Paper provided by CPB Netherlands Bureau for Economic Policy Analysis in its series CPB Discussion Paper with number 193.

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Date of creation: Nov 2011
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Handle: RePEc:cpb:discus:193

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  1. Graham Elliott & Allan Timmermann, 2008. "Economic Forecasting," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 3-56, March.
  2. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
  3. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
  4. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," NBER Working Papers 10254, National Bureau of Economic Research, Inc.
  5. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  6. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2010. "Variable Selection, Estimation and Inference for Multi-period Forecasting Problems," DNB Working Papers 250, Netherlands Central Bank, Research Department.
  7. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Thomas Sargent, 2005. "A, B, C’s, (and D’s) for understanding VARs," Working Paper 2005-09, Federal Reserve Bank of Atlanta.
  8. Coenraad N. Teulings & Nick Zubanov, 2010. "Is Economic Recovery a Myth? Robust Estimation of Impulse Responses," CESifo Working Paper Series 3027, CESifo Group Munich.
  9. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
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